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8 clients · secrets stay placeholders

JSON (mcpServers)Claude CodeCodexOpenCodeCursorVS CodeGemini CLIGoose

{
  "mcpServers": {
    "nlp": {
      "type": "http",
      "url": "https://api.brainiall.com/mcp/nlp/mcp"
    }
  }
}

claude mcp add --transport http nlp https://api.brainiall.com/mcp/nlp/mcp

[mcp_servers.nlp]
url = "https://api.brainiall.com/mcp/nlp/mcp"

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "nlp": {
      "type": "remote",
      "url": "https://api.brainiall.com/mcp/nlp/mcp",
      "enabled": true
    }
  }
}

{
  "mcpServers": {
    "nlp": {
      "type": "http",
      "url": "https://api.brainiall.com/mcp/nlp/mcp"
    }
  },
  "deeplink": "cursor://anysphere.cursor-deeplink/mcp/install?name=nlp&config=eyJ0eXBlIjoiaHR0cCIsInVybCI6Imh0dHBzOi8vYXBpLmJyYWluaWFsbC5jb20vbWNwL25scC9tY3AifQ%3D%3D"
}

{
  "servers": {
    "nlp": {
      "type": "http",
      "url": "https://api.brainiall.com/mcp/nlp/mcp"
    }
  }
}

{
  "mcpServers": {
    "nlp": {
      "httpUrl": "https://api.brainiall.com/mcp/nlp/mcp"
    }
  }
}

extensions:
  "nlp":
    enabled: true
    name: "nlp"
    type: streamable_http
    uri: "https://api.brainiall.com/mcp/nlp/mcp"
    timeout: 300

Quality 91 / 100strong

protocol75 · weight 25

warn
protocol.modernnewest supported version is 2025-11-25; 2026-07-28 not supported, older versions are deprecated until 2027-07-28
n/a
protocol.statelessonly applies to 2026-07-28 servers
pass
protocol.transportstreamable HTTP
n/a
protocol.list_ttlonly applies to 2026-07-28 servers

authorizationn/a · weight 15

n/a
auth.prm, auth.as_metadata, auth.cimdno remote uses OAuth
n/a
auth.secret_in_urlno templated URL

tool hygiene100 · weight 30

pass
tools.descriptionsevery tool has a description
pass
tools.description_lengthdescriptions are concise
pass
tools.schemasevery tool has an object input schema
pass
tools.annotations22 of 22 tools declare readOnlyHint or destructiveHint
pass
tools.directory_hintsevery tool declares readOnlyHint, destructiveHint, idempotentHint and openWorldHint
pass
tools.token_costabout 4,782 tokens to load every tool
pass
tools.api_dumptools are not a one-to-one API dump

stability100 · weight 15

pass
stability.changesno tool changes in 30 days
pass
stability.rug_pullno tool changed its meaning under the same name

dependenciesn/a · weight 15

n/a
deps.known_vulns, deps.mcp_sdk_version, deps.resolvableno npm or PyPI package

22 tools, about 4,782 tokens to load them all · tool set 01227389721e · checked 2026-10-20 04:09 UTC

Tool changes

No tool definition changes recorded. A server's first observation is its baseline; later probes record what changes.

Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. How it is computed.

Trust 80 / 100

no-repository

provenance55

liveness100

freshness85

hygiene80

+dns-namespace +website +reachable +uptime-100% ~updated-54d-ago -no-repository

Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed. How it is computed.

Endpoints

remote	auth	reachable	uptime 30d	p50	protocol	last ok
`https://api.brainiall.com/mcp/nlp/mcp` streamable-http	none	yes	100%	522 ms	2025-11-25	2026-10-20

Tools (22)

`analyze_sentiment`read-only	Analyze text sentiment. Returns positive/negative classification with confidence scores. Brainiall Sentiment engine-based with sub-10ms latency. Multiple domain-specific model variants available. Args: text: Text to analyze for sentiment (positive/negative). model: Model variant -- 'general' (default), 'financial', 'twitter'. Returns: dict with keys: - label (str): 'positive' or 'negative' - score (float 0-1): Confidence score for the predicted label - scores (dict): All label scores (positive, negative)
`analyze_toxicity`read-only	Analyze text for toxic content. Returns scores for 6 categories: toxic, severe_toxic, obscene, threat, insult, identity_hate. Each score is 0.0-1.0. BERT-based classifier with sub-15ms latency on GPU. Args: text: Text to analyze for toxicity (hate speech, insults, threats). Returns: dict with keys: - toxic (float 0-1): Overall toxicity score - severe_toxic (float 0-1): Severe toxicity score - obscene (float 0-1): Obscenity score - threat (float 0-1): Threat score - insult (float 0-1): Insult score - identity_hate (float 0-1): Identity-based hate score - is_toxic (bool): Whether text exceeds toxicity threshold
`answer_question`read-only	Answer a question using ONLY the supplied text; returns the supporting sentence(s) with character offsets. Replies found:false rather than guessing when the answer isn't present in the text. Args: text: The text/document to answer from. question: The question to answer. Returns: dict with keys: answer (str\|null), found (bool), supporting_spans (list of {text, start, end}).
`aspect_sentiment`read-only	Sentiment per aspect. Brainiall Aspect Sentiment engine. Splits the text into sentences mentioning each aspect, classifies each, aggregates.
`check_groundedness`read-only	Hallucination check: is a claim actually supported by a source text? Brainiall Groundedness engine. Returns {grounded, confidence, supporting_span, reason}.
`check_nlp_service`read-only	Check health status of NLP API services and loaded models. Returns: dict with keys: - status (str): 'healthy' or error state - models (dict): Loaded model status per capability - version (str): API version
`classify_text_custom`read-only	Zero-shot text classification — define your labels at call time. No training, no data upload. Brainiall Custom Classifier engine. Returns {top_label, scores, confidence}.
`detect_conversational_pii`read-only	Multi-turn PII detection with cross-turn coreference. Brainiall Conversational PII engine. Same surface text + type across turns gets the same entity_id.
`detect_language`read-only	Detect the language of text. Supports 176 languages using fastText. Sub-1ms inference latency. Returns ISO 639-1 codes with confidence scores. Args: text: Text to identify the language of. top_k: Number of top language predictions to return (default: 3). Returns: dict with keys: - language (str): Top predicted language ISO 639-1 code - confidence (float 0-1): Confidence for top prediction - predictions (list): Top-k predictions, each with: - language (str): ISO 639-1 code - confidence (float 0-1): Prediction confidence
`detect_pii`read-only	Detect personally identifiable information (PII) in text. Finds emails, phone numbers, SSNs, credit cards, IP addresses, and person names. Optionally returns redacted text with PII replaced by type labels (e.g. [EMAIL], [PHONE]). BERT-NER + regex ensemble. Args: text: Text to scan for personally identifiable information. redact: If true, return redacted text with PII replaced by [TYPE]. Returns: dict with keys: - pii_found (list): Detected PII items, each containing: - text (str): The PII value found - type (str): PII type (EMAIL, PHONE, SSN, CREDIT_CARD, IP, PERSON) - start (int): Character offset start - end (int): Character offset end - score (float 0-1): Detection confidence - count (int): Total PII items found - redacted_text (str\|null): Text with PII replaced (when redact=true) - has_pii (bool): Whether any PII was detected
`detect_prompt_injection`read-only	Classify a prompt before it reaches your LLM. Brainiall Prompt Shield engine. Returns category (jailbreak \| prompt_injection \| data_exfiltration \| impersonation \| none), severity, reason, confidence.
`detect_protected_material`read-only	Detect copyrighted text in user input — famous lyrics, literary openings, proprietary code. Brainiall Protected Material engine. Returns matched spans with source attribution.
`extract_entities`read-only	Extract named entities (NER) from text. Identifies persons, organizations, locations, and miscellaneous entities with span offsets and confidence scores. BERT-NER based with sub-50ms latency. Args: text: Text to extract named entities from. Returns: dict with keys: - entities (list): Detected entities, each containing: - text (str): Entity text - label (str): Entity type (PER, ORG, LOC, MISC) - start (int): Character offset start - end (int): Character offset end - score (float 0-1): Confidence score - count (int): Total number of entities found
`extract_key_phrases`read-only	Statistical key-phrase extraction — top-N ranked phrases. Brainiall Key Phrases engine. Pure-statistical (TF + position + casing + stopword filter), no ML cost.
`fraud_feedback`	Report the confirmed outcome of an event so the fraud model can be re-calibrated to your data. Args: event_id: The event identifier. label: 'fraud' \| 'legitimate' \| 'chargeback' \| 'dispute'. notes: Optional free-text notes. Returns: dict with keys: event_id (str), label (str), accepted (bool), feedback_id (int).
`fraud_score`read-only	Score a transaction or account event for fraud risk. Send whatever signals you have — all optional. Returns a 0-1 fraud probability, a risk level, the exact risk factors that drove the score (each with its weight, direction and a human-readable detail), and a recommended decision (allow\|review\|deny). Returns: dict with keys: fraud_probability (float), risk_level (str), decision (str), risk_score_points (float), risk_factors (list of {factor, weight, direction, detail}), decision_bands (dict).
`knowledge_ingest`	Ingest a document into a knowledge base: it is chunked, embedded and stored for you (managed RAG). Args: namespace: The knowledge-base namespace. text: The document text. title: Optional title. Returns: dict with keys: doc_id (str), n_chunks (int).
`knowledge_list_documents`read-only	List the documents stored in a knowledge base (most recent first). Args: namespace: The knowledge-base namespace. Returns: dict with keys: documents (list of {doc_id, title, ...}).
`knowledge_query`read-only	Retrieve the most relevant passages from a knowledge base plus (optionally) a grounded, cited answer. Returns found:false rather than a guess when the passages don't contain the answer. Args: namespace: The knowledge-base namespace. question: The natural-language question. top_k: How many passages to retrieve. rerank: Re-order retrieved passages before answering. synthesize: Also return a grounded answer. Returns: dict with keys: answer (str\|null), found (bool), passages (list), synthesized (bool), reranked (bool), ...
`link_entities_to_wikidata`read-only	Named-entity recognition + canonical linking to Wikidata Q-ids. Brainiall Entity Linker engine. Disambiguates 'Apple' the company from 'apple' the fruit.
`summarize_text`read-only	Summarize text — extractive (verbatim key sentences in original order) or abstractive (concise rewrite). Args: text: The text to summarize. mode: 'abstractive' or 'extractive'. max_length: Target maximum length of the summary, in words. Returns: dict with the summary (key: summary) plus word/char counts.
`translate_text`read-only	Translate text between 100+ languages. Args: text: The text to translate. target_lang: Target language code. source_lang: Source language code; omit to auto-detect. Returns: dict with the translated text (key: translated_text) and the detected source language if auto-detected.

Schemas: list_tools.

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Official server.json

{
  "name": "com.brainiall/nlp",
  "title": "Brainiall NLP",
  "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
  "remotes": [
    {
      "url": "https://api.brainiall.com/mcp/nlp/mcp",
      "type": "streamable-http"
    }
  ],
  "version": "1.0.0",
  "websiteUrl": "https://brainiall.com",
  "description": "Sentiment, toxicity, entity extraction, PII, translation, summary, QA, fraud scoring, safety audit."
}